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Mastering Elasticsearch 5.x

You're reading from   Mastering Elasticsearch 5.x Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786460189
Length 428 pages
Edition 3rd Edition
Languages
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Author (1):
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Bharvi Dixit Bharvi Dixit
Author Profile Icon Bharvi Dixit
Bharvi Dixit
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Table of Contents (13) Chapters Close

Preface 1. Revisiting Elasticsearch and the Changes FREE CHAPTER 2. The Improved Query DSL 3. Beyond Full Text Search 4. Data Modeling and Analytics 5. Improving the User Search Experience 6. The Index Distribution Architecture 7. Low-Level Index Control 8. Elasticsearch Administration 9. Data Transformation and Federated Search 10. Improving Performance 11. Developing Elasticsearch Plugins 12. Introducing Elastic Stack 5.0

Altering Apache Lucene scoring


In Chapter 2, The Improved Query DSL, we discussed the changes in default scoring inside Elasticsearch as well as Apache Lucene. We also covered the new default text scoring algorithm, BM25, in detail. But apart from BM25 and TF-IDF, there are some additional similarity models available in Lucene since the release of Apache Lucene 4.0 in 2012, which basically allows you to alter the default algorithm and also to choose a different scoring formula for our documents. In this section, we will take a deeper look at these similarity scoring algorithms offered by Lucene and how these features were incorporated into Elasticsearch.

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